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-exploiting optimization algorithms will be used to improve the performance of the numerical methods also for this class of problems. As postdoc, you will principally carry out research. A certain amount of
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series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is
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descriptors of spatial distribution in the field of materials science (e.g., Voronoi tessellations, particle-particle distances, etc.)? What are appropriate algorithms for efficient quantification of spatial
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. The following education, experience and expertise are required: solid knowledge in machine learning, optimization, or algorithm development programming experience, preferably in Python In addition, the following
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and significant piece of information to the right point of computation (or actuation) at the correct moment in time. To address this challenge, you will focus on developing theoretical and algorithmic
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, C/C++, Java. JavaScript), especially in design, analysis and implementation of geometric algorithms (computational geometry, map-based web interfaces, GIS). It will be considered a merit if you also